---
title: "Single Column (Scrolling)"
output: 
  flexdashboard::flex_dashboard:
    orientation: rows
    social: menu
    source_code: embed
---

```{r setup, include=FALSE}
library(flexdashboard)
library(plotly)
library(covid19italy)
library(ggplot2)
library(dplyr)
italy_total2 <- italy_total %>%
  arrange(date) %>%
  mutate(diff_hospitalized_with_symptoms = hospitalized_with_symptoms - lag(hospitalized_with_symptoms, default = first(hospitalized_with_symptoms))) %>%
  mutate(diff_intensive_care = intensive_care - lag(intensive_care, default = first(intensive_care))) %>%
  mutate(diff_total_hospitalized = total_hospitalized - lag(total_hospitalized, default = first(total_hospitalized))) %>%
  mutate(diff_home_confinement = home_confinement - lag(home_confinement, default = first(home_confinement))) %>%
  mutate(diff_cumulative_positive_cases = cumulative_positive_cases - lag(cumulative_positive_cases, default = first(cumulative_positive_cases))) %>%
  mutate(diff_daily_positive_cases = daily_positive_cases - lag(daily_positive_cases, default = first(daily_positive_cases))) %>%
  mutate(diff_recovered = recovered - lag(recovered, default = first(recovered))) %>%
  mutate(diff_death = death - lag(death, default = first(death))) %>%
  mutate(diff_cumulative_cases = cumulative_cases - lag(cumulative_cases, default = first(cumulative_cases))) %>%
  mutate(diff_total_test = total_tests - lag(total_tests, default = first(total_tests)))

italy_total2[2:11] <- NULL

```

Column {data-width=650}
-----------------------------------------------------------------------

### Chart A

```{r}

plot_ly(data = italy_total2,
        x = ~ date,
        y = ~ log(diff_total_test),
        name = 'Daily Tests',
        color = '#1f77b4',
        type = 'scatter',
        mode = '‘lines') %>%
  add_trace( y = ~ log(diff_death),
             name = "Daily Deaths",
             color = '#E41317') %>%
  add_trace(y = ~ log(diff_cumulative_positive_cases),
            name = 'Daily Positive Cases',
            color = 'forestgreen') %>%
  layout(title = "Italy - Distribution of Covid19 Cases daily",
         legend = list(x = 0.1, y = 0.9),
         yaxis = list(title = "Number of Cases per day on a log scale"),
         xaxis = list(title = "Source: Italy Department of Civil Protection"))
```

Column {data-width=350}
-----------------------------------------------------------------------

### Chart B

```{r}
plot_ly(data = italy_total2,
        x = ~ date,
        y = ~ diff_cumulative_cases,
        name = 'Active',
        fillcolor = '#1f77b4',
        type = 'scatter',
        mode = 'none',
        stackgroup = 'one') %>%
  add_trace( y = ~ diff_death,
             name = "Death",
             fillcolor = '#E41317') %>%
  add_trace(y = ~ diff_recovered,
            name = 'Recovered',
            fillcolor = 'forestgreen') %>%
  layout(title = "Italy - Distribution of Covid19 Cases",
         legend = list(x = 0.1, y = 0.9),
         yaxis = list(title = "Number of Cases"),
         xaxis = list(title = "Source: Italy Department of Civil Protection"))

```

### Chart C

```{r}
italy_province %>%
  filter(date == max(date), region_name == "Lombardia") %>%
  plot_ly(labels = ~province_name, values = ~new_cases,
          textinfo="label+percent",
          type = 'pie') %>%
  layout(title = "Lombardia - New Cases Distribution by Province in Lombardia") %>%
  hide_legend()
```

\newpage

Row
-----------------------------------------------------------------------

### New Deaths

```{r}
  valueBox(tail(italy_total2$diff_death, n = 1), 
           icon = "fa-skull")
```

### New Cases

```{r}
  valueBox(tail(italy_total2$diff_cumulative_cases, n = 1), 
           icon = "fa-virus-slash")
```

### New Tests

```{r}
  valueBox(tail(italy_total2$diff_total_test, n = 1), 
           icon = "fa-briefcase-medical")
```

Row 
-----------------------------------------------------------------------

### New Deaths

```{r}
gauge(tail(italy_total2$diff_death, n = 1), min = 0, max = max(italy_total2$diff_death), symbol = ' ', gaugeSectors(
  success = c(0, 300), warning = c(301, 600), danger = c(601, max(italy_total2$diff_death))
))
```

### New Cases

```{r}
gauge(tail(italy_total2$diff_cumulative_cases, n = 1), min = 0, max = max(italy_total2$diff_cumulative_cases), symbol = ' ', gaugeSectors(
  success = c(0, 1000), warning = c(1001, 4000), danger = c(4001, max(italy_total2$diff_cumulative_positive_cases))
))
```

### New Tests

```{r}
gauge(tail(italy_total2$diff_total_test, n = 1), min = 0, max = max(italy_total2$diff_total_test), symbol = ' ', gaugeSectors(
  success = c(40001, max(italy_total2$diff_total_test) ), warning = c(20001, 40000), danger = c(0, 20000))
)
```